1.0 2.0 3.0 ... 579.0 580.0 583.0
ancillary_surface_classification_flag
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
7-state surface type classification computed from a mask built with MODIS and GlobCover data.
- flag_meanings :
-
open_ocean land continental_water aquatic_vegetation continental_ice_snow floating_ice salted_basin
- flag_values :
-
[0, 1, 2, 3, 4, 5, 6]
- institution :
-
European Space Agency
- long_name :
-
surface classification
- source :
-
MODIS/GlobCover
- standard_name :
-
status_flag
- valid_max :
-
6
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
correction_flag
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Quality flag for corrections.
- flag_meanings :
-
good bad
- flag_values :
-
[0, 1]
- long_name :
-
quality flag for corrections
- standard_name :
-
status_flag
- valid_max :
-
1
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
cross_track_angle
(pass_num, num_lines)
float64
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
Angle with respect to true north of the cross-track direction to the right of the spacecraft velocity vector.
- long_name :
-
cross-track angle from true north
- units :
-
degrees
- valid_max :
-
359999999
- valid_min :
-
0
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
cross_track_distance
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Distance of sample from nadir. Negative values indicate the left side of the swath, and positive values indicate the right side of the swath.
- long_name :
-
cross track distance
- units :
-
m
- valid_max :
-
75000.0
- valid_min :
-
-75000.0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
dac
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Model estimate of the effect on sea surface topography due to high frequency air pressure and wind effects and the low-frequency height from inverted barometer effect (inv_bar_cor). This value is subtracted from the ssh_karin and ssh_karin_2 to compute ssha_karin and ssha_karin_2, respectively. Use only one of inv_bar_cor and dac.
- institution :
-
LEGOS/CNES/CLS
- long_name :
-
dynamic atmospheric correction
- source :
-
MOG2D
- units :
-
m
- valid_max :
-
12000
- valid_min :
-
-12000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
depth_or_elevation
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Ocean depth or land elevation above reference ellipsoid. Ocean depth (bathymetry) is given as negative values, and land elevation positive values.
- institution :
-
European Space Agency
- long_name :
-
ocean depth or land elevation
- source :
-
Altimeter Corrected Elevations, version 2
- units :
-
m
- valid_max :
-
10000
- valid_min :
-
-12000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
distance_to_coast
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Approximate distance to the nearest coast point along the Earth surface.
- institution :
-
European Space Agency
- long_name :
-
distance to coast
- source :
-
MODIS/GlobCover
- units :
-
m
- valid_max :
-
21000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
doppler_centroid
(pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
Doppler centroid (in hertz or cycles per second) estimated by KaRIn.
- long_name :
-
doppler centroid estimated by KaRIn
- units :
-
1/s
- valid_max :
-
30000
- valid_min :
-
-30000
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
dynamic_ice_flag
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Dynamic ice flag for the location of the KaRIn measurement.
- flag_meanings :
-
no_ice probable_ice ice
- flag_values :
-
[0, 1, 2]
- institution :
-
EUMETSAT
- long_name :
-
dynamic ice flag
- source :
-
EUMETSAT Ocean and Sea Ice Satellite Applications Facility
- standard_name :
-
status_flag
- valid_max :
-
2
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
geoid
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Geoid height above the reference ellipsoid with a correction to refer the value to the mean tide system, i.e. includes the permanent tide (zero frequency).
- long_name :
-
geoid height
- source :
-
EGM2008 (Pavlis et al., 2012)
- standard_name :
-
geoid_height_above_reference_ellipsoid
- units :
-
m
- valid_max :
-
1500000
- valid_min :
-
-1500000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
heading_to_coast
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Approximate compass heading (0-360 degrees with respect to true north) to the nearest coast point.
- long_name :
-
heading to coast
- units :
-
degrees
- valid_max :
-
35999
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
height_cor_xover
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Height correction from KaRIn crossover calibration. To apply this correction the value of height_cor_xover should be added to the value of ssh_karin, ssh_karin_2, ssha_karin, and ssha_karin_2.
- long_name :
-
height correction from KaRIn crossovers
- units :
-
m
- valid_max :
-
100000
- valid_min :
-
-100000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
ice_conc
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Concentration of sea ice from model.
- institution :
-
EUMETSAT
- long_name :
-
concentration of sea ice
- source :
-
EUMETSAT Ocean and Sea Ice Satellite Applications Facility
- standard_name :
-
sea_ice_area_fraction
- units :
-
%
- valid_max :
-
10000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
internal_tide_hret
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Coherent internal ocean tide. This value is subtracted from the ssh_karin and ssh_karin_2 to compute ssha_karin and ssha_karin_2, respectively.
- long_name :
-
coherent internal tide (HRET)
- source :
-
Zaron (2019)
- units :
-
m
- valid_max :
-
2000
- valid_min :
-
-2000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
internal_tide_sol2
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Coherent internal tide.
- long_name :
-
coherent internal tide (Model 2)
- source :
-
TBD
- units :
-
m
- valid_max :
-
2000
- valid_min :
-
-2000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
inv_bar_cor
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Estimate of static effect of atmospheric pressure on sea surface height. Above average pressure lowers sea surface height. Computed by interpolating ECMWF pressure fields in space and time. The value is included in dac. To apply, add dac to ssha_karin and ssha_karin_2 and subtract inv_bar_cor.
- long_name :
-
static inverse barometer effect on sea surface height
- units :
-
m
- valid_max :
-
2000
- valid_min :
-
-2000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
iono_cor_gim_ka
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Equivalent vertical correction due to ionosphere delay. The reported sea surface height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height.
- institution :
-
JPL
- long_name :
-
ionosphere vertical correction
- source :
-
Global Ionosphere Maps
- units :
-
m
- valid_max :
-
0
- valid_min :
-
-5000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
latitude_avg_ssh
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Latitude of measurement [-80,80]. Positive latitude is North latitude, negative latitude is South latitude. This value may be biased away from a nominal grid location if some of the native, unsmoothed samples were discarded during processing.
- long_name :
-
weighted average latitude of samples used to compute SSH
- standard_name :
-
latitude
- units :
-
degrees_north
- valid_max :
-
80000000
- valid_min :
-
-80000000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
load_tide_fes
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Geocentric load tide height. The effect of the ocean tide loading of the Earth's crust. This value has already been added to the corresponding ocean tide height value (ocean_tide_fes).
- institution :
-
LEGOS/CNES
- long_name :
-
geocentric load tide height (FES)
- source :
-
FES2014b (Carrere et al., 2016)
- units :
-
m
- valid_max :
-
2000
- valid_min :
-
-2000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
load_tide_got
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Geocentric load tide height. The effect of the ocean tide loading of the Earth's crust. This value has already been added to the corresponding ocean tide height value (ocean_tide_got).
- institution :
-
GSFC
- long_name :
-
geocentric load tide height (GOT)
- source :
-
GOT4.10c (Ray, 2013)
- units :
-
m
- valid_max :
-
2000
- valid_min :
-
-2000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
longitude_avg_ssh
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Longitude of measurement. East longitude relative to Greenwich meridian. This value may be biased away from a nominal grid location if some of the native, unsmoothed samples were discarded during processing.
- long_name :
-
weighted average longitude of samples used to compute SSH
- standard_name :
-
longitude
- units :
-
degrees_east
- valid_max :
-
359999999
- valid_min :
-
0
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
mean_dynamic_topography
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Mean dynamic topography above the geoid.
- institution :
-
CNES/CLS
- long_name :
-
mean dynamic topography
- source :
-
CNES_CLS_18
- units :
-
m
- valid_max :
-
30000
- valid_min :
-
-30000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
mean_dynamic_topography_uncert
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Accuracy of the mean dynamic topography.
- institution :
-
CNES/CLS
- long_name :
-
mean dynamic topography accuracy
- source :
-
CNES_CLS_18
- units :
-
m
- valid_max :
-
10000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
mean_sea_surface_cnescls
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Mean sea surface height above the reference ellipsoid. The value is referenced to the mean tide system, i.e. includes the permanent tide (zero frequency).
- institution :
-
CNES/CLS
- long_name :
-
mean sea surface height (CNES/CLS)
- source :
-
CNES_CLS_15
- units :
-
m
- valid_max :
-
1500000
- valid_min :
-
-1500000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
mean_sea_surface_cnescls_uncert
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Accuracy of the mean sea surface height (mean_sea_surface_cnescls).
- institution :
-
CNES/CLS
- long_name :
-
mean sea surface height accuracy (CNES/CLS)
- source :
-
CNES_CLS_15
- units :
-
m
- valid_max :
-
10000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
mean_sea_surface_dtu
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Mean sea surface height above the reference ellipsoid. The value is referenced to the mean tide system, i.e. includes the permanent tide (zero frequency).
- institution :
-
DTU
- long_name :
-
mean sea surface height (DTU)
- source :
-
DTU18
- units :
-
m
- valid_max :
-
1500000
- valid_min :
-
-1500000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
mean_sea_surface_dtu_uncert
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Accuracy of the mean sea surface height (mean_sea_surface_dtu)
- institution :
-
DTU
- long_name :
-
mean sea surface height accuracy (DTU)
- source :
-
DTU18
- units :
-
m
- valid_max :
-
10000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
mean_wave_direction
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Mean sea surface wave direction.
- institution :
-
Meteo France
- long_name :
-
mean sea surface wave direction
- source :
-
Meteo France Wave Model (MF-WAM)
- units :
-
degree
- valid_max :
-
36000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
mean_wave_period_t02
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Sea surface wind wave mean period from model spectral density second moment.
- institution :
-
Meteo France
- long_name :
-
sea surface wind wave mean period
- source :
-
Meteo France Wave Model (MF-WAM)
- standard_name :
-
sea_surface_wave_significant_period
- units :
-
s
- valid_max :
-
100
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
model_dry_tropo_cor
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Equivalent vertical correction due to dry troposphere delay. The reported sea surface height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height.
- institution :
-
ECMWF
- long_name :
-
dry troposphere vertical correction
- source :
-
European Centre for Medium-Range Weather Forecasts
- units :
-
m
- valid_max :
-
-15000
- valid_min :
-
-30000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
model_wet_tropo_cor
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Equivalent vertical correction due to wet troposphere delay from weather model data. The reported pixel height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height (ssh_karin_2) results in the uncorrected sea surface height.
- institution :
-
ECMWF
- long_name :
-
wet troposphere vertical correction from weather model data
- source :
-
European Centre for Medium-Range Weather Forecasts
- units :
-
m
- valid_max :
-
0
- valid_min :
-
-10000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
num_pt_avg
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Number of native unsmoothed, beam-combined KaRIn samples averaged.
- long_name :
-
number of samples averaged
- units :
-
1
- valid_max :
-
289
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
obp_ref_surface
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Height (relative to the reference ellipsoid) of the reference surface used by the KaRIn on-board processor.
- long_name :
-
height of reference surface used by on-board-processor
- units :
-
m
- valid_max :
-
150000000
- valid_min :
-
-15000000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
ocean_tide_eq
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Equilibrium long-period ocean tide height. This value has already been added to the corresponding ocean tide height values (ocean_tide_fes and ocean_tide_got).
- long_name :
-
equilibrium long-period ocean tide height
- units :
-
m
- valid_max :
-
2000
- valid_min :
-
-2000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
ocean_tide_fes
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Geocentric ocean tide height. Includes the sum total of the ocean tide, the corresponding load tide (load_tide_fes) and equilibrium long-period ocean tide height (ocean_tide_eq).
- institution :
-
LEGOS/CNES
- long_name :
-
geocentric ocean tide height (FES)
- source :
-
FES2014b (Carrere et al., 2016)
- units :
-
m
- valid_max :
-
300000
- valid_min :
-
-300000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
ocean_tide_got
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Geocentric ocean tide height. Includes the sum total of the ocean tide, the corresponding load tide (load_tide_got) and equilibrium long-period ocean tide height (ocean_tide_eq).
- institution :
-
GSFC
- long_name :
-
geocentric ocean tide height (GOT)
- source :
-
GOT4.10c (Ray, 2013)
- units :
-
m
- valid_max :
-
300000
- valid_min :
-
-300000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
ocean_tide_non_eq
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Non-equilibrium long-period ocean tide height. This value is reported as a relative displacement with repsect to ocean_tide_eq. This value can be added to ocean_tide_eq, ocean_tide_fes, or ocean_tide_got, or subtracted from ssha_karin and ssha_karin_2, to account for the total long-period ocean tides from equilibrium and non-equilibrium contributions.
- institution :
-
LEGOS/CNES
- long_name :
-
non-equilibrium long-period ocean tide height
- source :
-
FES2014b (Carrere et al., 2016)
- units :
-
m
- valid_max :
-
2000
- valid_min :
-
-2000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
orbit_alt_rate
(pass_num, num_lines)
float32
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
Orbital altitude rate with respect to the mean sea surface.
- long_name :
-
orbital altitude rate with respect to mean sea surface
- units :
-
m/s
- valid_max :
-
3500
- valid_min :
-
-3500
| Bytes |
11.29 MiB |
25.36 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
orbit_qual
(pass_num, num_lines)
float32
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
Orbit quality flag.
- long_name :
-
orbit quality flag
- standard_name :
-
status_flag
- valid_max :
-
1
- valid_min :
-
0
| Bytes |
11.29 MiB |
25.36 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
phase_bias_ref_surface
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Height (relative to the reference ellipsoid) of the reference surface used for phase bias calculation during L1B processing.
- long_name :
-
height of reference surface used for phase bias calculation
- units :
-
m
- valid_max :
-
150000000
- valid_min :
-
-15000000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
polarization_karin
(pass_num, num_lines, num_sides)
object
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
H denotes co-polarized linear horizontal, V denotes co-polarized linear vertical.
- long_name :
-
polarization for each side of the KaRIn swath
| Bytes |
45.16 MiB |
101.42 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
object |
numpy.ndarray |
|
 |
pole_tide
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Geocentric pole tide height. The total of the contribution from the solid-Earth (body) pole tide height, the ocean pole tide height, and the load pole tide height (i.e., the effect of the ocean pole tide loading of the Earth's crust).
- long_name :
-
geocentric pole tide height
- source :
-
Wahr (1985) and Desai et al. (2015)
- units :
-
m
- valid_max :
-
2000
- valid_min :
-
-2000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rad_cloud_liquid_water
(pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
Integrated cloud liquid water content from radiometer measurements.
- long_name :
-
liquid water content from radiometer
- source :
-
Advanced Microwave Radiometer
- standard_name :
-
atmosphere_cloud_liquid_water_content
- units :
-
kg/m^2
- valid_max :
-
2000
- valid_min :
-
0
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rad_surface_type_flag
(pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
Flag indicating the validity and type of processing applied to generate the wet troposphere correction (rad_wet_tropo_cor). A value of 0 indicates that open ocean processing is used, a value of 1 indicates coastal processing, and a value of 2 indicates that rad_wet_tropo_cor is invalid due to land contamination.
- flag_meanings :
-
open_ocean coastal_ocean land
- flag_values :
-
[0, 1, 2]
- long_name :
-
radiometer surface type flag
- source :
-
Advanced Microwave Radiometer
- standard_name :
-
status_flag
- valid_max :
-
2
- valid_min :
-
0
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rad_tmb_187
(pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
Main beam brightness temperature measurement at 18.7 GHz. Value is unsmoothed (along-track averaging has not been performed).
- long_name :
-
radiometer main beam brightness temperature at 18.7 GHz
- source :
-
Advanced Microwave Radiometer
- standard_name :
-
toa_brightness_temperature
- units :
-
K
- valid_max :
-
25000
- valid_min :
-
13000
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rad_tmb_238
(pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
Main beam brightness temperature measurement at 23.8 GHz. Value is unsmoothed (along-track averaging has not been performed).
- long_name :
-
radiometer main beam brightness temperature at 23.8 GHz
- source :
-
Advanced Microwave Radiometer
- standard_name :
-
toa_brightness_temperature
- units :
-
K
- valid_max :
-
25000
- valid_min :
-
13000
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rad_tmb_340
(pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
Main beam brightness temperature measurement at 34.0 GHz. Value is unsmoothed (along-track averaging has not been performed).
- long_name :
-
radiometer main beam brightness temperature at 34.0 GHz
- source :
-
Advanced Microwave Radiometer
- standard_name :
-
toa_brightness_temperature
- units :
-
K
- valid_max :
-
28000
- valid_min :
-
15000
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rad_water_vapor
(pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
Integrated water vapor content from radiometer measurements.
- long_name :
-
water vapor content from radiometer
- source :
-
Advanced Microwave Radiometer
- standard_name :
-
atmosphere_water_vapor_content
- units :
-
kg/m^2
- valid_max :
-
15000
- valid_min :
-
0
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rad_wet_tropo_cor
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Equivalent vertical correction due to wet troposphere delay from radiometer measurements. The reported pixel height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height (ssh_karin) results in the uncorrected sea surface height.
- long_name :
-
wet troposphere vertical correction from radiometer data
- source :
-
Advanced Microwave Radiometer
- units :
-
m
- valid_max :
-
0
- valid_min :
-
-10000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rain_flag
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Flag indicates that signal is attenuated, probably from rain.
- flag_meanings :
-
no_rain probable_rain rain
- flag_values :
-
[0, 1, 2]
- long_name :
-
rain flag
- standard_name :
-
status_flag
- valid_max :
-
2
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
rain_rate
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Rain rate from weather model.
- institution :
-
ECMWF
- long_name :
-
rain rate from weather model
- source :
-
European Centre for Medium-Range Weather Forecasts
- units :
-
mm/hr
- valid_max :
-
200
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
sc_altitude
(pass_num, num_lines)
float64
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
Altitude of the KMSF origin.
- long_name :
-
altitude of KMSF origin
- standard_name :
-
height_above_reference_ellipsoid
- units :
-
m
- valid_max :
-
2000000000
- valid_min :
-
0
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
sc_pitch
(pass_num, num_lines)
float64
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
KMSF attitude pitch angle; positive values move the KMSF +x axis up.
- long_name :
-
pitch of the spacecraft
- standard_name :
-
platform_pitch_angle
- units :
-
degrees
- valid_max :
-
1800000
- valid_min :
-
-1799999
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
sc_roll
(pass_num, num_lines)
float64
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
KMSF attitude roll angle; positive values move the +y antenna down.
- long_name :
-
roll of the spacecraft
- standard_name :
-
platform_roll_angle
- units :
-
degrees
- valid_max :
-
1800000
- valid_min :
-
-1799999
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
sc_yaw
(pass_num, num_lines)
float64
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
KMSF attitude yaw angle relative to the nadir track. The yaw angle is a right-handed rotation about the nadir (downward) direction. A yaw value of 0 deg indicates that the KMSF +x axis is aligned with the horizontal component of the Earth-relative velocity vector. A yaw value of 180 deg indicates that the spacecraft is in a yaw-flipped state, with the KMSF -x axis aligned with the horizontal component of the Earth-relative velocity vector.
- long_name :
-
yaw of the spacecraft
- standard_name :
-
platform_yaw_angle
- units :
-
degrees
- valid_max :
-
1800000
- valid_min :
-
-1799999
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
sea_state_bias_cor
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Sea state bias correction to ssh_karin. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height. The wind_speed_karin value is used to compute this quantity.
- long_name :
-
sea state bias correction to height
- source :
-
TBD
- units :
-
m
- valid_max :
-
0
- valid_min :
-
-6000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
sea_state_bias_cor_2
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Sea state bias correction to ssh_karin_2. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height. The wind_speed_karin_2 value is used to compute this quantity.
- long_name :
-
sea state bias correction to height
- source :
-
TBD
- units :
-
m
- valid_max :
-
0
- valid_min :
-
-6000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
sig0_cor_atmos_model
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Atmospheric correction to sigma0 from weather model data as a linear power multiplier (not decibels). sig0_cor_atmos_model is already applied in computing sig0_karin_2.
- institution :
-
ECMWF
- long_name :
-
two-way atmospheric correction to sigma0 from model
- source :
-
European Centre for Medium-Range Weather Forecasts
- units :
-
1
- valid_max :
-
10.0
- valid_min :
-
1.0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
sig0_cor_atmos_rad
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Atmospheric correction to sigma0 from radiometer data as a linear power multiplier (not decibels). sig0_cor_atmos_rad is already applied in computing sig0_karin.
- long_name :
-
two-way atmospheric correction to sigma0 from radiometer data
- source :
-
Advanced Microwave Radiometer
- units :
-
1
- valid_max :
-
10.0
- valid_min :
-
1.0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
sig0_karin
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Normalized radar cross section (sigma0) from KaRIn in real, linear units (not decibels). The value may be negative due to noise subtraction. The value is corrected for instrument calibration and atmospheric attenuation. Radiometer measurements provide the atmospheric attenuation (sig0_cor_atmos_rad).
- long_name :
-
normalized radar cross section (sigma0) from KaRIn
- standard_name :
-
surface_backwards_scattering_coefficient_of_radar_wave
- units :
-
1
- valid_max :
-
10000000.0
- valid_min :
-
-1000.0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
sig0_karin_2
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Normalized radar cross section (sigma0) from KaRIn in real, linear units (not decibels). The value may be negative due to noise subtraction. The value is corrected for instrument calibration and atmospheric attenuation. A meteorological model provides the atmospheric attenuation (sig0_cor_atmos_model).
- long_name :
-
normalized radar cross section (sigma0) from KaRIn
- standard_name :
-
surface_backwards_scattering_coefficient_of_radar_wave
- units :
-
1
- valid_max :
-
10000000.0
- valid_min :
-
-1000.0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
sig0_karin_qual
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Quality flag for sigma0 from KaRIn.
- flag_meanings :
-
good bad
- flag_values :
-
[0, 1]
- long_name :
-
quality flag for sigma0 from KaRIn.
- standard_name :
-
status_flag
- valid_max :
-
1
- valid_min :
-
0
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
sig0_karin_uncert
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
1-sigma uncertainty on sigma0 from KaRIn.
- long_name :
-
1-sigma uncertainty on sigma0 from KaRIn
- units :
-
1
- valid_max :
-
1000.0
- valid_min :
-
0.0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
simulated_error_baseline_dilation
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- long_name :
-
Error due to baseline mast dilation
- units :
-
m
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
simulated_error_karin
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- long_name :
-
KaRIn error
- units :
-
m
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
simulated_error_orbital
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- long_name :
-
Error due to orbital perturbations
- units :
-
m
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
simulated_error_phase
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- long_name :
-
Error due to phase
- units :
-
m
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
simulated_error_roll
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- long_name :
-
Error due to roll
- units :
-
m
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
simulated_error_timing
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- long_name :
-
Timing error
- units :
-
m
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
simulated_true_ssh_karin
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Height of the sea surface free of measurement errors.
- long_name :
-
sea surface height
- standard_name :
-
sea surface height above reference ellipsoid
- units :
-
m
- valid_max :
-
150000000
- valid_min :
-
-15000000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
solid_earth_tide
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Solid-Earth (body) tide height. The zero-frequency permanent tide component is not included.
- long_name :
-
solid Earth tide height
- source :
-
Cartwright and Taylor (1971) and Cartwright and Edden (1973)
- units :
-
m
- valid_max :
-
10000
- valid_min :
-
-10000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
ssh_karin
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Fully corrected sea surface height measured by KaRIn. The height is relative to the reference ellipsoid defined in the global attributes. This value is computed using radiometer measurements for wet troposphere effects on the KaRIn measurement (e.g., rad_wet_tropo_cor and sea_state_bias_cor).
- long_name :
-
sea surface height
- standard_name :
-
sea surface height above reference ellipsoid
- units :
-
m
- valid_max :
-
150000000
- valid_min :
-
-15000000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
ssh_karin_2
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Fully corrected sea surface height measured by KaRIn. The height is relative to the reference ellipsoid defined in the global attributes. This value is computed using model-based estimates for wet troposphere effects on the KaRIn measurement (e.g., model_wet_tropo_cor and sea_state_bias_cor_2).
- long_name :
-
sea surface height
- standard_name :
-
sea surface height above reference ellipsoid
- units :
-
m
- valid_max :
-
150000000
- valid_min :
-
-15000000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
ssh_karin_uncert
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
1-sigma uncertainty on the sea surface height from the KaRIn measurement.
- long_name :
-
sea surface height anomaly uncertainty
- units :
-
m
- valid_max :
-
60000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
ssha_karin
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Sea surface height anomaly from the KaRIn measurement = ssh_karin - mean_sea_surface_cnescls - solid_earth_tide - ocean_tide_fes – internal_tide_hret - pole_tide - dac.
- long_name :
-
sea surface height anomaly
- units :
-
m
- valid_max :
-
1000000
- valid_min :
-
-1000000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
ssha_karin_2
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Sea surface height anomaly from the KaRIn measurement = ssh_karin_2 - mean_sea_surface_cnescls - solid_earth_tide - ocean_tide_fes – internal_tide_hret - pole_tide - dac.
- long_name :
-
sea surface height anomaly
- units :
-
m
- valid_max :
-
1000000
- valid_min :
-
-1000000
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
ssha_karin_qual
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Quality flag for the SSHA from KaRIn.
- flag_meanings :
-
good bad
- flag_values :
-
[0, 1]
- long_name :
-
sea surface height quality flag
- standard_name :
-
status_flag
- valid_max :
-
1
- valid_min :
-
0
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
swh_karin
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Significant wave height from KaRIn volumetric correlation.
- long_name :
-
significant wave height from KaRIn
- standard_name :
-
sea_surface_wave_significant_height
- units :
-
m
- valid_max :
-
25000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
swh_karin_qual
(pass_num, num_lines, num_pixels)
float64
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Quality flag for significant wave height from KaRIn.
- flag_meanings :
-
good bad
- flag_values :
-
[0, 1]
- long_name :
-
quality flag for significant wave height from KaRIn.
- standard_name :
-
status_flag
- valid_max :
-
1
- valid_min :
-
0
| Bytes |
1.57 GiB |
3.52 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
swh_karin_uncert
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
1-sigma uncertainty on significant wave height from KaRIn.
- long_name :
-
1-sigma uncertainty on significant wave height from KaRIn
- units :
-
m
- valid_max :
-
25000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
swh_model
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Significant wave height from model.
- institution :
-
ECMWF
- long_name :
-
significant wave height from wave model
- source :
-
European Centre for Medium-Range Weather Forecasts
- standard_name :
-
sea_surface_wave_significant_height
- units :
-
m
- valid_max :
-
30000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
swh_sea_state_bias
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Significant wave height used in sea state bias correction.
- long_name :
-
SWH used in sea state bias correction
- units :
-
m
- valid_max :
-
25000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
time
(pass_num, num_lines)
datetime64[ns]
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
Time of measurement in seconds in the UTC time scale since 1 Jan 2000 00:00:00 UTC. [tai_utc_difference] is the difference between TAI and UTC reference time (seconds) for the first measurement of the data set. If a leap second occurs within the data set, the attribute leap_second is set to the UTC time at which the leap second occurs.
- leap_second :
-
YYYY-MM-DDThh:mm:ssZ
- long_name :
-
time in UTC
- standard_name :
-
time
- tai_utc_difference :
-
35.0
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
datetime64[ns] |
numpy.ndarray |
|
 |
time_tai
(pass_num, num_lines)
datetime64[ns]
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
Time of measurement in seconds in the TAI time scale since 1 Jan 2000 00:00:00 TAI. This time scale contains no leap seconds. The difference (in seconds) with time in UTC is given by the attribute [time:tai_utc_difference].
- long_name :
-
time in TAI
- standard_name :
-
time
- tai_utc_difference :
-
[Value of TAI-UTC at time of first record]
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
datetime64[ns] |
numpy.ndarray |
|
 |
velocity_heading
(pass_num, num_lines)
float64
dask.array<chunksize=(1, 6491), meta=np.ndarray>

- comment :
-
Angle with respect to true north of the horizontal component of the spacecraft Earth-relative velocity vector. A value of 90 deg indicates that the spacecraft velocity vector pointed due east. Values between 0 and 90 deg indicate that the velocity vector has a northward component, and values between 90 and 180 deg indicate that the velocity vector has a southward component.
- long_name :
-
heading of the spacecraft Earth-relative velocity vector
- units :
-
degrees
- valid_max :
-
359999999
- valid_min :
-
0
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491) |
(1, 6491) |
| Count |
5474 Tasks |
456 Chunks |
| Type |
float64 |
numpy.ndarray |
|
 |
wind_speed_karin
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Wind speed from KaRIn computed from sig0_karin.
- long_name :
-
wind speed from KaRIn
- source :
-
TBD
- standard_name :
-
wind_speed
- units :
-
m/s
- valid_max :
-
65000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
wind_speed_karin_2
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Wind speed from KaRIn computed from sig0_karin_2.
- long_name :
-
wind speed from KaRIn
- source :
-
TBD
- standard_name :
-
wind_speed
- units :
-
m/s
- valid_max :
-
65000
- valid_min :
-
0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
wind_speed_model_u
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Eastward component of the atmospheric model wind vector at 10 meters.
- institution :
-
ECMWF
- long_name :
-
u component of model wind
- source :
-
European Centre for Medium-Range Weather Forecasts
- standard_name :
-
eastward_wind
- units :
-
m/s
- valid_max :
-
30000
- valid_min :
-
-30000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
wind_speed_model_v
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Northward component of the atmospheric model wind vector at 10 meters.
- institution :
-
ECMWF
- long_name :
-
v component of model wind
- source :
-
European Centre for Medium-Range Weather Forecasts
- standard_name :
-
northward_wind
- units :
-
m/s
- valid_max :
-
30000
- valid_min :
-
-30000
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
wind_speed_rad
(pass_num, num_lines, num_sides)
float32
dask.array<chunksize=(1, 6491, 2), meta=np.ndarray>

- comment :
-
Wind speed from radiometer measurements.
- long_name :
-
wind speed from radiometer
- source :
-
Advanced Microwave Radiometer
- standard_name :
-
wind_speed
- units :
-
m/s
- valid_max :
-
65000
- valid_min :
-
0
| Bytes |
22.58 MiB |
50.71 kiB |
| Shape |
(456, 6491, 2) |
(1, 6491, 2) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |
x_factor
(pass_num, num_lines, num_pixels)
float32
dask.array<chunksize=(1, 6491, 71), meta=np.ndarray>

- comment :
-
Radiometric calibration X factor as a linear power ratio.
- long_name :
-
radiometric calibration X factor as a composite value for the X factors of the +y and -y channels
- units :
-
1
- valid_max :
-
1.0000000200408773e+20
- valid_min :
-
0.0
| Bytes |
801.67 MiB |
1.76 MiB |
| Shape |
(456, 6491, 71) |
(1, 6491, 71) |
| Count |
5930 Tasks |
456 Chunks |
| Type |
float32 |
numpy.ndarray |
|
 |